Asset Liability Modeling

• Computational Finance Overview
• Monte Carlo Simulation
• Time-Series Analysis
• Portfolio Optimization and Analysis
• Energy Trading
• Asset Liability Modeling

MATLAB helps you develop and integrate asset-liability modeling (ALM) applications at significant cost savings over enterprise ALM software. You can build custom analytics that analyze and forecast assets and liabilities to manage risk and to facilitate solvency and regulatory compliance, of particular relevance to the insurance industry.

Value Complex Liabilities

To analyze and project liabilities, you use MATLAB with its optimization, portfolio analysis, Monte Carlo, and cash-flow capabilities to:

• Obtain asset values from the market via importing data directly from data providers
• Analyze and aggregate cash flows
• Select and optimize replicate portfolios which approximate scenario-dependent payoffs
• Accommodate skewness and kurtosis
• Backtest and perform what-if analysis
• Forecast mortality risk
• Model influencing factors such as GDP using econometric methods like vector autoregression

Develop Asset-Liability Models to Facilitate Decision Making

Use the forecasting capabilities and optimization solvers in MATLAB to develop asset-liability models and optimize your investment strategies. From a single environment,
you can:

• Hedge by buying (or selling) options and structured products
• Facilitate cash flow and duration matching
• Find an optimal asset portfolio to back up liabilities
• Calculate returns of optimal assets
• Restructure portfolios when liabilities change
• Study evolution of assets over time to predict market value and potential losses